# Center for Genomic Editing and Recording: Development and Application of Next-Generation Genome and Epigenome Editing Methods to Advance the Study and Treatment of Human Disease

> **NIH NIH RM1** · WHITEHEAD INSTITUTE FOR BIOMEDICAL RES · 2022 · $2,500,000

## Abstract

CENTER FOR GENOME EDITING AND RECORDING: PROJECT SUMMARY
Recent advances in DNA sequencing and bioinformatics have generated vast numbers of sequence variants
associated with disease that, in principle, hold the keys to breakthroughs in preventive medicine and
therapeutic intervention. However, realizing the promise of personalized medicine will require accurate
manipulation of DNA sequences and gene expression as well as interrogation of the functional consequences
of sequence variants at a scale and level of accuracy not currently possible.
 The Center for Genome Editing and Recording (CGER) will address these challenges by creating
technologies to detect, alter and record the sequence and output of the genome in individual cells and tissues.
The CGER will exploit the programmable DNA binding and nickase activity of CRISPR-Cas proteins as well as
engineered zinc finger and TALE proteins to create a new generation of tools to precisely engineer the genome
and epigenome. These platforms will enable high-precision engineering of both the nuclear and mitochondrial
genomes as well as heritable silencing or activation of messenger RNAs, long noncoding RNA and a host of
other regulatory elements such as enhancers and insulator regions. Critically, these alterations can be made
without introducing double stranded breaks to DNA, thereby avoiding DNA toxicity and minimizing reliance on
complex and difficult-to-control endogenous DNA repair pathways. Collectively, these technologies will usher in
a new era of safer, high precision and multiplexed genome and epigenome editing.
 In addition, we will exploit these platforms to develop higher-level multichannel molecular recorders that
will allow us to track and reconstruct the life history of cells in an in vivo setting. We will add the ability to follow
cells in space and time as well as record the history of their past cellular states to the existing phylogenetic
lineage tracing systems pioneered in the previous embodiment of this Center.
 The center will be led by a team that collectively has a remarkable track record of developing bold,
impactful new tools to expand their precision, efficacy, safety and scope, and finally exploiting these new
capabilities to develop novel strategies to explore fundamental biological and biomedical problems. Our
multidisciplinary team has a rich history of working together, which has been greatly accelerated by the CEGS
structure in a manner that would simply not be possible if each co-PI had been working on similar problems in
isolation. Leveraging the capabilities of the Whitehead Institute, MIT, The Broad Institute, Harvard University,
Harvard Medical School, The Lewis Sigler Institute for Integrative Genomics at Princeton and the
Massachusetts General Hospital, we aim to create transformative capabilities and have access to state-of-the-
art research facilities as well as resources for training, education and outreach that will attract diverse talent to
the field of g...

## Key facts

- **NIH application ID:** 10408424
- **Project number:** 2RM1HG009490-06
- **Recipient organization:** WHITEHEAD INSTITUTE FOR BIOMEDICAL RES
- **Principal Investigator:** Brittany S. Adamson
- **Activity code:** RM1 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $2,500,000
- **Award type:** 2
- **Project period:** 2017-08-08 → 2027-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10408424

## Citation

> US National Institutes of Health, RePORTER application 10408424, Center for Genomic Editing and Recording: Development and Application of Next-Generation Genome and Epigenome Editing Methods to Advance the Study and Treatment of Human Disease (2RM1HG009490-06). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10408424. Licensed CC0.

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